Robotics Software Engineer

Sr. Software Developer - Robotics at Unbox Robotics About the Role We are looking for an experienced Robot Software & AMR Engineer to design, architect, and deploy autonomous navigation and software systems for Autonomous Mobile Robots (AMRs) and industrial mobile robotic platforms. In this role, you will bridge foundational robot software engineering with real-world mobile autonomy—owning everything from core C++/ROS 2 module development to production-grade SLAM, local/global path planning, multi-sensor fusion, and fleet-level communication. Roles & Responsibilities Architect, build, and deploy production-grade software stacks for Autonomous Mobile Robots (AMRs), covering autonomy, localization, motion control, and fleet integration. Design, build, and maintain efficient, modular, and reusable C++ and Python code adhering to strict safety and performance constraints. Implement, tune, and benchmark SLAM algorithms, dynamic obstacle avoidance, and global/local trajectory planning for real-world AMR deployments in dynamic environments. Integrate, calibrate, and filter data from diverse sensors (LiDARs, Depth Cameras, IMUs, Wheel Encoders) using robust sensor fusion techniques. Develop and debug robot behavior logic using Behavior Trees (Nav2 BT) and Finite State Machines (FSMs) for complex industrial workflows and docking routines. Architect low-latency, resilient inter-process and edge-to-cloud communication pipelines (DDS, MQTT, TCP/IP, WebSockets) connecting AMRs to Fleet Management Systems (FMS). Build simulation environments, mock pipelines, and automated test benches in Gazebo/Webots to validate software releases before on-robot deployment. Profile runtime bottlenecks, analyze memory/CPU footprints on edge computing hardware (e.g., NVIDIA Jetson, industrial x86/ARM IPCs), and devise targeted optimizations. Identify edge-case failures on hardware, triage field issues, and lead root-cause analysis (RCA) to drive software reliability. Requirements Core Engineering: 2–5 years of hands-on experience in robot software engineering, specifically targeting mobile robotics or AMRs. Languages & Tooling: Strong proficiency in modern C++ (C++14/17/20) and Python; deep understanding of OOP design, memory management, data structures, and algorithms. Robotics Ecosystem: Hands-on expertise with ROS / ROS 2 (rclcpp, rclpy, composition, lifecycle nodes) and navigation frameworks (Nav2). Navigation & Autonomy: Strong practical working knowledge of: SLAM & Localization: Cartographer, RTAB-Map, Nav2 AMCL, GraphSLAM, and EKF/UKF sensor fusion. Planning & Control: A*, Dijkstra, Hybrid A*, DWA, TEB Local Planner, MPPI, and kinematic motion models (differential drive, omnidirectional, or Ackermann). Sensors & Hardware Interfaces: Proven track record interfacing and calibrating 2D/3D LiDARs, depth cameras (RealSense, Stereo), IMUs, and motor controller feedback over CAN, Serial, or Ethernet. Communication & Protocols: Strong understanding of DDS (CycloneDDS, FastDDS), MQTT, ZeroMQ, or WebSockets, balancing latency, throughput, and failover requirements. Environment & Build Tools: Fluent in Linux (Ubuntu), CMake, Bash scripting, Git, and hardware-in-the-loop (HIL) debugging. Software Quality: Solid experience with automated testing (GTest, PyTest), static analysis tools, and CI/CD pipelines. Good to Have Hands-on experience integrating AMRs with Fleet Management Systems (e.g., Open-RMF, VDA 5050 standard) or warehouse execution systems (WES/WMS). Practical experience designing autonomous precision docking routines (using ArUco markers, reflectors, or visual servoing). Knowledge of Perception, Computer Vision (OpenCV), and Deep Learning edge inference (TensorRT, ONNX) for semantic obstacle detection. Familiarity with functional safety standards for industrial mobile robots (e.g., ISO 3691-4) Experience with containerized deployments using Docker for edge robotics. Candidate Profile & Qualifications Education: B.E. / B.Tech / M.Tech in Computer Science, Robotics, Electronics, Mechatronics, Mechanical, or allied engineering domains. Mindset: Proven track record of thriving in fast-paced, high-ownership engineering environments. Problem Solving: Structured approach to root-cause debugging on real physical robots under constrained operational timelines. Work Location: Pune Work Mode: In Campus Salary Range: Competitive Salary